Simulation-based approach to general game playing

Proceedings of the National Conference on Artificial Intelligence

Volumn 1, Issue , 2008, Pages 259-264

  Finnsson, Hilmar ^a   Björnsson, Yngvi ^a  

^a REYKJAVIK UNIVERSITY   (Iceland)

Author keywords

[No Author keywords available]

Indexed keywords

AGENTS; ARTIFICIAL INTELLIGENCE; BIONICS; HEURISTIC ALGORITHMS; INTELLIGENT AGENTS;

ACTION SELECTIONS; GENERAL GAME PLAYING; HEURISTIC FUNCTIONS; HUMAN INTERVENTIONS; SIMULATION TECHNIQUES; TREE SEARCHES;

GAME THEORY;

EID: 57749181518     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. Auer, P.; Cesa-Bianchi, N.; and Fischer, P. 2002. Finite-time analysis of the multiarmed bandit problem. Machine Learning 47(2/3): 235-256.
2. Banerjee, B., and Stone, P. 2007. General game learning using knowledge transfer. In The 20th International Joint Conference on Arti cial Intelligence, 672-677.
3. Banerjee, B.; Kuhlmann, G.; and Stone, P. 2006. Value function transfer for General Game Playing. In ICML Workshop on Structural Knowledge Transfer for ML.
4. Clune, J. 2007. Heuristic evaluation functions for General Game Playing. In Proceedings of the Twenty-Second AAAI Conference on Arti cial Intelligence, 1134-1139.
5. Costa, V. S.; Damas, L.; Reis, R.; and Azevedo, R. 2006. YAP Prolog user s manual. Retrieved January 27, 2008, from http://www.ncc.up.pt/̃vsc/Yap/ documentation.html.
6. Coulom, R. 2006. Efficient selectivity and backup operators in Monte-Carlo tree search. In The 5th International Conference on Computers and Games (CG2006), 72-83.
7. Finnsson, H. 2007. CADIA-Player: A General Game Playing Agent. Master s thesis, Reykjav k′ University.
8. Gelly, S., and Silver, D. 2007. Combining online and offline knowledge in UCT. In Ghahramani, Z., ed., ICML, volume 227, 273-280. ACM.
9. Gelly, S.; Wang, Y.; Munos, R.; and Teytaud, O. 2006. Modification of UCT with patterns in Monte-Carlo Go. Technical Report 6062, INRIA.
10. Genesereth, M. R., and Fikes, R. E. 1992. Knowledge interchange format, version 3.0 reference manual. Technical Report Technical Report Logic-92-1, Stanford University.
11. Genesereth, M. R.; Love, N.; and Pell, B. 2005. General Game Playing: Overview of the AAAI competition. AI Magazine 26(2):62-72.
12. Kocsis, L., and Szepesvári, C. 2006. Bandit based Monte-Carlo planning. In European Conference on Machine Learning (ECML), 282-293.
13. Kuhlmann, G.; Dresner, K.; and Stone, P. 2006. Automatic heuristic construction in a complete general game player. In Proc. of the Twenty-First National Conference on Arti-cial Intelligence, 1457-62.
14. Love, N.; Hinrichs, T.; and Genesereth, M. 2006. General Game Playing: Game description language specification. Technical Report April 4 2006, Stanford University.
15. Pell, B. 1996. A strategic metagame player for general chess-like games. Computational Intelligence 12:177-198.
16. Reinefeld, A., and Marsland, T. A. 1994. Enhanced iterative-deepening search. IEEE Transactions on Pattern Analysis and Machine Intelligence 16(7):701-710.
17. Schaeffer, J. 1989. The history heuristic and alpha-beta search enhancements in practice. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-11(11):1203-1212
18. Schiffel, S., and Thielscher, M. 2007. Fluxplayer: A successful general game player. In Proc. of the Twenty-Second AAAI Conference on Arti cial Intelligence, 1191-1196.